Data Engineer — ML Data Pipelines for Autonomous Defense

Signal Processing Engineer (RF Processing & Analytics); Paris; Sur place; EUR 60 000 - 90 000; Plein temps

Résumé du poste

Harmattan AI seeks a Data Engineer to own the data layer for autonomous and scalable defense ML pipelines. You will ingest, decode, and store vast unstructured data, ensuring clean, versioned, training-ready datasets for modelers.

You will shape data processing from raw logs to curated training sets, enabling efficient model development. Based in Paris, Lausanne, or Zurich, you will collaborate with field, acquisition, and labeling teams, driving dataset construction, lineage, and optimized data

Qualifications

• Educational background in a STEM field or equivalent practical experience.
• Practical data engineering experience matters more than the specific degree.

Responsabilités

• Ingestion Pipeline: Ingest, decode, and store raw, unstructured field data from field logs.
• Multimodal Alignment: Align multiple data streams temporally and spatially for training.
• Curation: Transfer ingested data and public datasets into high-value data.
• Data & Labeling Requirements: Define data to gather, labeling, and manage workflows.
• Dataset Construction: Build task-specific datasets with cross-team collaboration.
• Versioning & Lineage: Version datasets and maintain reproducibility for runs.
• Storage & Formats: Store data in training-ready formats and manage storage tiers.
• Efficient Delivery: Deliver clean datasets and tools for loading to reduce IO bottlenecks.

Connaissances

Python

Data engineering

PyTorch

Formation

STEM degree

Outils

PyTorch

Description du poste

Harmattan AI seeks a Data Engineer to own the data layer for autonomous and scalable defense ML pipelines. You will ingest, decode, and store vast unstructured data, ensuring clean, versioned, training-ready datasets for modelers.

You will shape data processing from raw logs to curated training sets, enabling efficient model development. Based in Paris, Lausanne, or Zurich, you will collaborate with field, acquisition, and labeling teams, driving dataset construction, lineage, and optimized data